metadata
base_model: SI2M-Lab/DarijaBERT
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: darija_test4
results: []
darija_test4
This model is a fine-tuned version of SI2M-Lab/DarijaBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2337
- Accuracy: 0.9402
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.691 | 1.0 | 209 | 0.6551 | 0.6388 |
| 0.48 | 2.0 | 418 | 0.5391 | 0.8086 |
| 0.7983 | 3.0 | 627 | 0.6059 | 0.7105 |
| 0.7509 | 4.0 | 836 | 0.5645 | 0.7201 |
| 0.6031 | 5.0 | 1045 | 0.5616 | 0.7249 |
| 0.4155 | 6.0 | 1254 | 0.5425 | 0.8062 |
| 0.5307 | 7.0 | 1463 | 0.5160 | 0.7943 |
| 0.4064 | 8.0 | 1672 | 0.4301 | 0.8469 |
| 0.3983 | 9.0 | 1881 | 0.3789 | 0.8971 |
| 0.4016 | 10.0 | 2090 | 0.2337 | 0.9402 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1